Li Yizhang, Dong Xiaodi, Cao Guiyun, Guo Yongbin, Wang Zhongmin, Yang Xiuwei, Han Dongyue, Meng Zhaoqing
School of Electrical Engineering & Automation, Institute of Automation, Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory of UWB & THz of Shandong Academy of Sciences, Jinan 250100, China.
Traditional Chinese Medicine Research Institute, Shandong Hongjitang Pharmaceutical Group Co. Ltd, Jinan 250103, China.
J Anal Methods Chem. 2024 Nov 20;2024:3858763. doi: 10.1155/jamc/3858763. eCollection 2024.
Baicalin concentration is concerned in manufacture of scutellaria spray drying powder as a traditional Chinese medicine, and the quality control based on high-performance liquid chromatography is inconvenience. In this study, terahertz time domain spectroscopy was employed to achieve quality control of scutellaria spray drying powder; however, an acute difficulty was found that terahertz spectra overlapped due to the disturbance in both content matrix and measurement error. In this study, similar terahertz spectra of scutellaria spray drying powder were classified with the help of Gaussian mixture model and built a classifier based on probability feature instead of spectral features conventionally employed in previous investigations. To explore the feasibility of GMM, principal component analysis was given, indicating that it is possible to train GMM with original features and proper principal components. Probable advantage of training GMM based on PCA feature was discussed and so it was with the capacity of the model to identify the linear combined spectra by comparing the performance of GMM and a decision tree model. Above all, the reason why GMM shows potential in the analysis of TCM terahertz spectra was illustrated by comparing the thought of discriminative model and generative model. This study implied that generative model may have natural advantage of overcoming the inherent disturbance of terahertz spectroscopy, which would be promising in future studies.
黄芩苷浓度在中药黄芩喷雾干燥粉的生产中备受关注,而基于高效液相色谱的质量控制存在不便之处。本研究采用太赫兹时域光谱法实现黄芩喷雾干燥粉的质量控制;然而,发现了一个棘手的问题,即由于含量基质的干扰和测量误差,太赫兹光谱出现重叠。在本研究中,借助高斯混合模型对黄芩喷雾干燥粉相似的太赫兹光谱进行分类,并基于概率特征构建分类器,而非以往研究中常规使用的光谱特征。为探究高斯混合模型的可行性,进行了主成分分析,结果表明利用原始特征和适当的主成分训练高斯混合模型是可行的。讨论了基于主成分分析特征训练高斯混合模型的可能优势,并通过比较高斯混合模型和决策树模型的性能,探讨了该模型识别线性组合光谱的能力。最重要的是,通过比较判别模型和生成模型的思路,阐述了高斯混合模型在中药太赫兹光谱分析中显示出潜力的原因。本研究表明,生成模型在克服太赫兹光谱固有干扰方面可能具有天然优势,这在未来研究中具有广阔前景。